|
Presenting Author |
Title |
Talk/Poster |
|
Abbasi-Asl, Reza |
The DeepTune framework for modeling and characterizing neurons in visual cortex |
poster |
|
Aenugu, Sneha |
A neural reinterpretation of long short-term memory |
poster |
|
Aghamohammadi, Cina |
Unbiased partitioning of spiking variability to reveal decision computations |
poster |
|
Ahmad, Subutai |
Sparsity in the neocortex, and its implications for machine learning |
poster |
|
Akaishi, Rei |
Multiscale neural computations and exploitation/exploration behavior |
poster |
|
Aldarondo, Diego E |
Analyzing the neural dynamics underlying hierarchical motor control in a virtual rodent |
poster |
|
Almanza, Mark |
A comparison of neural network and penalized regression approaches for fast neurochemical detection in humans and rodents |
poster |
|
Amsalem, Oren |
Analytical reduction of detailed nonlinear neuron models for biologically-inspired machine learning |
poster |
|
Anokhin, Konstantin |
Towards principles of neuromorphic memory—Selective allocation of associative memory in the mouse brain circuits |
poster |
|
Artoni, Pietro |
Deep learning of spontaneous arousal fluctuations detects early cholinergic defects across neurodevelopmental mouse models and patients |
poster |
|
Arun, SP |
Towards a dialogue between machine vision and biological vision |
poster |
|
Bae, Hyojin |
Lessons from artificial neural network for studying coding principles of biological neural network |
poster |
|
Barabasi, Daniel L |
A genetically-encoded connectome model for neural network evolution |
talk |
|
Bengio, Yoshua |
Towards bridging the gap between backprop and neuroscience |
talk |
|
Beniaguev, David |
Single cortical neurons as deep artificial neural networks |
poster |
|
Benjamin, Asaf |
Neural representations of social information in the mouse prefrontal cortex |
poster |
|
Beuth, Frederik |
Predicting how the brain solves different visual task classes |
poster |
|
Blakeman, Sam |
A complementary learning systems approach to temporal difference learning |
poster |
|
Bohm, Clifford |
Can evolution help us discover artificial intelligence? |
poster |
|
Bordelon, Blake A |
Optimal spectral properties of population codes for noise robust readout |
poster |
|
Borgohain, Satya |
Self-organising neural network hierarchy |
poster |
|
Borthakur, Ayon |
Lifelong learning in the wild using Intel Loihi |
talk |
|
Braun, Lukas |
Online learning of neural computations from sparse temporal feedback |
poster |
|
Cadena, Santiago A |
How well do deep neural networks trained on object recognition characterize the mouse visual system? |
poster |
|
Chapman, William G |
Trajectory prediction in a biologically inspired network |
poster |
|
Chapochnikov, Nikolai |
Mechanistic model of a neural circuit implementing whitening in olfaction |
poster |
|
Chartier, Thomas F |
Symmetry inference, an important feature for AI systems |
poster |
|
Chen, Jiang-fan |
Calcium signal from M1 neural populations support the cross-day neuroprosthetic learning with stable neuroplasticity mapping |
poster |
|
Chklovskii, Dmitri |
A visual motion detector—From the connectome to a theory of transformation learning |
talk |
|
Churchland, Anne |
Movements, decisions, and wholistic behavior |
talk |
|
Collman, Forrest C |
Complexity of cortical cell types signaling pathways |
poster |
|
Conwell, Colin |
Mouse brain in the modeling zoo—Neural architecture search and taskonomy for unveiling the representational structure of rodent visual cortex |
poster |
|
Cornille, Nathan |
Improving representation learning with pervasive internal regression (PIR) |
poster |
|
Cowley, Benjamin R |
From vision to decision—Deep neural network modeling of visuomotor transformations during social interaction |
poster |
|
Cueva, Christopher |
Emergence of functional and structural properties of the head direction system by optimization of recurrent neural networks |
poster |
|
Czegel, Daniel |
Emergent evolutionary dynamics over recurrent neural computations |
poster |
|
Davidson, Guy |
Investigating simple object representations in model-free deep reinforcement learning |
poster |
|
Deny, Stéphane |
An empirical study of inductive biases in deep neural networks |
poster |
|
Diao, Huitian |
Predicting single cell-fate decisions in CD8 T cells responding to viral infection |
poster |
|
Dorkenwald, Sven M |
Binary and analog variation of synapses between cortical pyramidal neurons |
poster |
|
Doron, Michael |
Using prior knowledge to automatically discover interesting phenomena in computational models |
poster |
|
Dyballa, Luciano |
Deep artificial neural networks—Little brains or big retinas? |
talk |
|
Finn, Chelsea |
How not to create a robot's mind |
talk |
|
Fomins, Aleksejs |
Information-theoretic pipeline for uncovering whole-brain spatio-temporal patterns from mesoscopic calcium recordings |
poster |
|
Fraser, Maia |
Temporo-spatial hierarchy and reinforcement learning - enabling richer alignment with the environment for more general AI |
talk |
|
Gardner, Daniel |
Are neural circuits and computations evolutionarily conserved? New potential designs for AI systems |
poster |
|
Gazula, Harshvardhan |
Attention-coupled saliency enhances the interpretability of recurrent models |
poster |
|
Geadah, Victor |
Single-neuron nonlinearities and their impact on learning dynamics of recurrent networks |
talk |
|
Genkin, Mikhail |
Discovering interpretable models of population dynamics from neural activity recordings |
poster |
|
George, Dileep |
Recursive cortical network—A generative vision model with deep grounding in neuroscience |
talk |
|
Ghazizadeh, Elham |
Learned attractor dynamics for sequential working memory |
poster |
|
Goeltz, Julian |
Fast and deep neuromorphic learning with time-to-first-spike coding |
poster |
|
Gold, Carl |
Shallow learning in spiking neural networks using dendritic connection rules based on topography |
poster |
|
Golden, Ryan |
Hippocampal indexing at the onset of cortical up states promotes consolidation and prevents retroactive interference |
poster |
|
Gordon, Jeremy R |
Long distance relationships without time travel—Boosting the performance of a sparse predictive autoencoder in sequence modeling |
poster |
|
Goudar, Vishwa |
Elucidating the neural mechanisms of learning-to-learn |
talk |
|
Han, Yena |
Unsupervised learning of latent variables from continuously changing data |
poster |
|
Hawkins, Jeff |
How the brain uses references frames to learn a model of the world, and why AI needs to do the same |
talk |
|
Heiney, Kristine A |
Computational behavior of biological neural networks through the lens of criticality |
poster |
|
Huang, Ben S |
OpenCortex—An integrated platform for deconstructing cortex-wide cognitive networks in behaving mice |
poster |
|
Huse Ramstad, Ola |
Neural network models informed by network electrophysiology |
poster |
|
Jacob, Georgin |
Do deep neural networks see the way we do? |
poster |
|
Jain, Shailee |
Natural language encoding models for fMRI reveal distinct patterns of semantic integration across cortex |
poster |
|
Jang, Jaeson |
Emergence of face-selective neurons in untrained deep neural networks |
poster |
|
Jang, Jaeson |
Emergence of number selectivity in untrained deep neural networks |
poster |
|
Janik, Romuald A |
Entropy from machine learning―Defining entropic characteristics of deep neural networks and complexity of datasets |
poster |
|
Jensen, Kristopher T |
Self-supervised learning for multisensory integration in biologically inspired networks |
poster |
|
Ji, Ni |
A biological neural network balancing exploration versus exploitation during foraging |
talk |
|
Jordan, Jakob |
Conductance-based dendrites perform reliability-weighted opinion pooling |
poster |
|
Kadkhodaie, Zahra |
Learning and utilizing a prior for natural images with deep neural networks |
poster |
|
Kalidindi, Hari T |
Quasi-oscillatory dynamics in motor cortex are consistent with a feedback-driven system |
poster |
|
Katti, Harish |
Cracking CAPTCHAs using a separable neural code |
poster |
|
Kenyon, Garrett |
Using models of cortical development based on sparse coding to discriminate between real and synthetically generated faces |
poster |
|
Kim, Edward |
Inhibitory and excitatory top-down feedback for visual perception |
poster |
|
Kim, Jineun |
Rapid, biphasic CRF neuronal responses encode positive and negative valence |
poster |
|
Klindt, David A |
Unsupervised learning of image manifolds with mutual information |
poster |
|
Klukas, Mirko |
Representing non-Euclidean spaces and abstract data structures with grid cells and place cells |
poster |
|
Konkle, Talia |
Emergence of multiple visual areas without a feature hierarchy |
talk |
|
Koo, Peter |
Neural networks that learn robust features are more robust and interpretable |
poster |
|
Kording, Konrad |
Geometrical ways of thinking about deep learning and brain activities |
talk |
|
Kornfeld, Joergen M |
A connectomic substrate of credit assignment in basal ganglia reinforcement learning |
poster |
|
Kosoy, Eliza |
Children’s intrinsic exploration of mazes compared to exploration algorithms |
poster |
|
Koulakov, Alex |
Genomic bottleneck approach to faster learning |
poster |
|
Koulakov, Alex |
Reinforcement learning basis of social conflict |
poster |
|
Kowadlo, Gideon |
Use of an artificial hippocampal algorithm for one-shot and continual learning |
poster |
|
Krotov, Dmitry |
Bio-inspired hashing for unsupervised similarity search |
poster |
|
Kudithipudi, Dhireesha |
Brain-inspired local metaplasticity for lifelong learning |
talk |
|
Kumar, M Ganesh |
Learning multiple cue-reward location associations with a reservoir computing model and temporal difference error-modulated Hebbian plasticity |
poster |
|
Kvitsiani, Duda |
Normative account for choice history bias in mice and humans |
poster |
|
Kwapich, Robert S |
Unsupervised identification of brain-state dynamics in mice from multi-channel LFP recordings |
poster |
|
Lacefield, Clay |
A proposed neural network architecture for autonomous control based on the mammalian cortico-striatal system |
poster |
|
Lai Lucy |
A computational division of labor for motor skill learning |
talk |
|
Landau, Andrew T |
Learning rules mediating complex computation in biological neurons |
poster |
|
Langdon, Christopher M |
Multi-area recurrent neural network model of decision-making |
poster |
|
Launay, Julien |
Computer vision and feedback alignment methods |
poster |
|
Lavin, Alexander |
Integration of human-like covert-overt attention with probabilistic convolutional neural nets |
poster |
|
Leadholm, Niels |
Hierarchical feature binding in convolutional neural networks confers resistance to adversarial attacks |
poster |
|
Li, Ye |
Orientation and color tuning of gamma range activity in human visual cortex |
poster |
|
Lim, Woochang |
Influence of various temporal recoding on Pavlovian eyeblink conditioning in the cerebellum |
poster |
|
Lin, Yen-Chu |
Cognitive influences on fixational eye movements (FEM) during visual discrimination |
poster |
|
Linsley, Drew A |
The function of contextual illusions |
poster |
|
Lipshutz, David |
A biologically plausible neural circuit for slow feature analysis |
poster |
|
Lipshutz, David |
A canonical correlation analysis model of the cortical microcircuit |
poster |
|
Liu, Yanhe Y |
A prefrontal top-down circuit underlying inference-based flexible decision-making |
poster |
|
Liu, Yue |
Unifying spectral models of reinforcement learning in the Laplace domain |
poster |
|
Logiaco, Laureline |
A thalamocortical model solves sequencing tasks more robustly than backpropagation-trained RNNs |
talk |
|
Lowe, Scott C |
Higher-order activation functions |
poster |
|
Lu, Jinghao |
Cortical representations of painful facial stimuli and vibrotactile touch-mediated-analgesia |
poster |
|
Luther, Kyle |
A label-based measure of invariance in neural networks |
poster |
|
Madireddy, Sandeep |
Metalearning for spiking neurons |
poster |
|
Makino, Hiroshi |
Cortical representations of theoretical variables in reinforcement learning |
poster |
|
Man, Kingson |
Truth or consequences—Homeostatic self-regulation in artificial neural networks |
poster |
|
Marino, Joseph L |
Predictive coding, variational autoencoders, and biological connections |
poster |
|
Martin, Erwann |
Spiking equilibrium propagation for intrinsic learning hardware |
talk |
|
Masset, Paul |
A computational architecture for early olfactory processing |
poster |
|
Meadows, Austin |
Sniffing out immune cell infiltration in solid tumors |
poster |
|
Mitchell, Kevin |
The evolution of agency—Or how to give a robot a soul |
talk |
|
Moldwin, Toviah |
The Gradient Clusteron—A gradient-based method for supervised learning via local dendritic nonlinearities and structural plasticity |
poster |
|
Moya-Sanchez, Eduardo Ulises |
Deterministic CNN layer inspired on V1-cortex cells with illumination invariance and rotation equivariance response |
poster |
|
Nejatbakhsh, Amin |
Correlating non-simultaneous neural data |
poster |
|
Nejatbakhsh, Amin |
Joint segmentation and labeling of C. elegans neurons |
poster |
|
Niv, Yael |
Hippocampus-orbitofrontal interactions in building a cognitive map of task space |
talk |
|
Olshausen, Bruno |
Sparse coding, manifold flattening and persistence as organizing principles of visual representation |
talk |
|
Paiton, Dylan M |
Response surfaces reveal invariances and selectivity in V1 neurons |
poster |
|
Panda, Priyadarshini |
Towards scalable spike-based learning with backward residual connections |
talk |
|
Pandey, Biraj |
Random feature networks with neuronal tuning |
poster |
|
Pao, Gerald |
Manifold networks of brain activity embeddings that generate naturalistic behaviors |
poster |
|
Parde, Connor J |
Concurrent representational codes in DCNNs trained for face identification |
poster |
|
Parthasarathy, Nikhil |
Self-supervised learning of a visual texture representation for cortical area V2 |
poster |
|
Pearlmutter, Barak |
Learning to learn compositionally without gradient descent by gradient descent |
talk |
|
Pedigo, Benjamin D |
A quantitative comparison of a complete connectome to artificial intelligence architectures |
poster |
|
Pereira, Talmo D |
Deep generative modeling of biological sensorimotor transformations via imitation learning |
poster |
|
Philippides, Andrew |
Insect-inspired autonomous visual navigation—Smart tricks from small brains |
talk |
|
Pitkow, Xaq |
Rational thoughts in neural codes |
talk |
|
Pontes-Filho, Sidney |
Towards the evolution of spiking neural networks for self-supervision with neuroplasticity |
poster |
|
Puelma Touzel, Maximilian |
Neuro-inspired reinforcement learning for episodic tasks |
poster |
|
Qin, Shanshan |
Contrastive similarity matching for supervised learning |
poster |
|
Rahimi Moghaddam, Shima |
Learning from temporally smooth information |
poster |
|
Rawat, Shivang |
Generalized ORGaNICs―Towards a unifying framework for neural dynamics |
poster |
|
Reimers, Mark |
The modular mind gives way to the dynamic brain |
poster |
|
Ricci, Matthew |
"Kura-Net"—An end-to-end differentiable featuring binding algorithm using the Kuramoto model |
poster |
|
Rinkus, Gerard J |
A combinatorial population code can simultaneously transmit the full similarity (likelihood) distribution via an atemporal first-spike code |
poster |
|
Roach, James P |
Inhibitory circuit structure and the temporal dynamics of decision-making. |
poster |
|
Robinson, Brian S |
A cortical spiking network model for semantic representation and replay-based association acquisition |
poster |
|
Ryu, Jungwon |
Brain-like autoencoder that learns latent covariance structure |
poster |
|
Safron, Adam |
Brains as Kalman variational autoencoding heterarchies―The conscious turbo-code |
poster |
|
Sarkar, Aakash |
Scale-dependent relationships in natural language |
poster |
|
Savin, Cristina |
Computing and learning in the presence of neural noise |
talk |
|
Saxena, Shreya |
The hypothesis of low trajectory tangling predicts motor cortex population activity across movement speeds |
poster |
|
Schossau, Jory |
Evolution of curiosity |
poster |
|
Segert, Simon |
Relaxed graph matching for analogy and reasoning |
poster |
|
Sejnowski, Terrence |
Strong inhibitory signaling underlies stable temporal dynamics and working memory in spiking neural networks |
talk |
|
Sekhar, Sudarshan |
A hybrid neural network / Kalman filter decoder improves brain-computer interface performance |
poster |
|
Shen, Yang |
A correspondence between normalization strategies in artificial and real neural networks |
talk |
|
Shi, Jianghong |
CNN MouseNet―Biologically constrained convolutional neural network model
for mouse visual cortex |
poster |
|
Shi, Yanliang |
Spatiotemporal neural correlations and dynamics in neural networks with spatial network architectures |
poster |
|
Shin, Jae Hoon |
Deep interaction between reinforcement learning algorithms and human reinforcement learning |
poster |
|
Shuvaev, Sergey |
Neural networks with motivation |
talk |
|
Singh, Satpreet Harcharan |
Understanding biological plume tracking behavior using deep reinforcement-learning |
poster |
|
Sizikova, Elena |
Word recognition in humans and deep neural networks |
poster |
|
Sokol, Piotr A |
Unexpected benefits of learning with neural oscillations—Stable backpropagation with limit cycles |
poster |
|
Solla, Sara A |
A Bayesian theory of supervised learning |
talk |
|
Srinivasan, Shyam |
A winner-take-all mechanism balances the trade-off between neuronal variability and discrimination |
poster |
|
Sussillo, David |
Universality and individuality in neural dynamics across large populations of recurrent networks |
talk |
|
Tamari, Ronen |
Language (re)modelling—Towards embodied inductive biases for language understanding |
poster |
|
Tanaka, Hidenori |
From deep learning to mechanistic understanding in neuroscience—Tthe structure of retinal prediction |
poster |
|
Tapson, Jonathan |
Brain-inspired computing and the algorithm problem |
poster |
|
Tepper, Mariano H |
Learning neural Nyström representations |
poster |
|
Teti, Michael |
Can sparse coding account for non-classical receptive field effects in V1 simple cells? |
poster |
|
Tolias, Andreas |
A less artificial intelligence |
talk |
|
Toosi, Tahereh |
Symbiotic learning of feedforward and feedback networks |
talk |
|
Topalovic, Uros |
Deep learning methods for exploring human cognition |
poster |
|
Tran, Ngoc |
DeepNose—Using artificial neural networks to represent the space of odorants |
talk |
|
Tresp, Volker |
The tensor brain |
talk |
|
Tripp, Bryan P |
Simulated environment for naturalistic mouse models |
poster |
|
Turcu, Denis |
Using a Sparse RNN for dynamic binary classification |
poster |
|
Versace, Elisabetta |
Priors for generalization—Insights from newborn chicks |
poster |
|
Vogelstein, Joshua |
A biological implementation of lifelong learning in the pursuit of artificial general intelligence |
poster |
|
Wanner, Adrian A |
How recurrent is the network of strong connections in the neocortex? |
poster |
|
Xie, Marjorie |
The significance of sparse representations in cerebellum-like networks |
poster |
|
Yamakawa, Hiroshi |
Understanding the computational meaning of the neocortical interrarea signals |
poster |
|
Yamashiro, Kotaro |
Decoding complex sensory stimuli from neuronal activity of rat somatosensory cortex |
poster |
|
Yang, Guangyu Robert |
Evolving the olfactory system |
poster |
|
Yang, Runzhe |
Unsupervised feature discovery by neural networks with disynaptic recurrent inhibition |
talk |
|
Yilmaz, Hakan |
Inverse graphics explains population responses in body-selective regions of the primate inferotemporal cortex |
poster |
|
Zapp, Soren J |
Inference of functional network structure using matrix factorization |
poster |
|
Zhu, Hanlin |
Acquiring long-term, large-scale neural data to accelerate discoveries at the intersection of Neuroscience and AI |
poster |
|
Zhu, Yuqing |
Addition of neocortical features permits successful training of spiking neuronal network models |
poster |